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4.4 How digital technologies were leveraged for targeted poverty alleviation
Poverty targeting
Digital technologies improved the accuracy and effectiveness of poverty alleviation by enhancing targeting, selection of antipoverty measures, implementation of assistance projects, and funds utilization. Guizhou province took the lead in using digital technologies and an integrated data platform for poverty reduction work. The Poverty Alleviation and Development Office of Guizhou put into use the Guizhou Poverty Alleviation Cloud platform, which pooled information from 7.48 million registered poor (as of 2012) and applied geographic information systems to locate the poor at the village level. It provided data updates with personal computer and app terminals instead of paper forms, bringing about data sharing among departments and timely announcement of policies and specific actions, such as matching of employment vacancies to job seekers. More than 409,000 users of the platform include poverty alleviation department officials at each administrative level, persons in charge of local assistance, the first secretary, and the local poverty reduction team.
The platform also records poverty alleviation project types, start and end dates, and the number of beneficiaries, which supports decision-making for industry development, employment, migration and relocation, and other assistance adapted to household conditions. The distribution and payment of various subsidies and livelihood funds to each poor household can also be searched. It presents the specific uses of the central and local Anti-Poverty Fund and integration funds, and comprehensively tracks fund use and investment by beneficiaries. It can also screen out households that do not meet the requirements for poverty registration, and thus help optimize the efficiency of poverty alleviation resources use.
Inclusive business models of e-commerce platforms
E-commerce platforms have greatly lowered the threshold for small and micro businesses to enter large markets. The division of labor brought by the e-commerce industry created employment opportunities for the poor in various fields, including processing, logistics, packaging, and customer service. More than 5 percent of total employment in China is in e-commerce. E-commerce platform companies such as Alibaba and JD.com have proactively developed inclusive business models and incorporated philanthropic programs to enhance market access, income growth, and capacity building in poverty-stricken areas (World Bank and Alibaba Group 2019). In 2019, online retail sales in 832 poverty-stricken counties reached 239.2 billion yuan (MOFCOM 2020a). The National Rural E-commerce Comprehensive Demonstration Project has contributed to the income growth of nearly 3 million registered impoverished households (NDRC 2018b). By 2020, turnover of products from national-level poverty-stricken counties reached more than 200 billion yuan on the Alibaba platform (Alibaba Group 2020). Online retailing has created over 28 million jobs in rural China (CIECC 2018c). In addition, rural e-commerce also benefits the most vulnerable groups such as women and the elderly. From April 2015 to March 2017, 1.12 million people from 765 national-level poverty-stricken counties took 559 online courses offered by Alibaba, which can be accessed from about 92 percent of these counties (Alibaba Group 2017d).
Digital inclusive finance
The digital financial institutions established by internet companies make use of transaction data from e-commerce platforms to accurately analyze the transaction behaviors of poor households or micro businesses and portray their credit ratings. The poor population and micro businesses in rural areas could have access to financial services such as digital credit, mobile payment, and internet insurance. The application of digital technology to financing helps provide new solutions to the “last mile” problem of inclusive finance, contributing to lessening the impact of insufficient mortgages for the poor. However, the accuracy of digital models in depicting borrower risk profiles should not be overestimated, and the roles of other actors are essential. Relevant regulatory reforms (for example, requiring separate licenses for the personal credit reporting businesses of fintech conglomerates, refining personal data protection law, and others) are underway.
The number of online banking accounts in rural areas totaled 612 million in 2018, covering
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63.22 percent of the rural populatione; the number of annual online banking payments topped 10.21 billion; and payment receipt services provided by banks for rural electronic transactions reached 578.34 billion yuan (People’s Bank of China 2019f). Financial institutions cooperate with internet companies to further expand the financial coverage of rural populations.
Since its establishment in 2015, China’s first cloud computing–based commercial bank, MYbank, has provided contactless loans to more than 4 million clients in 146 poverty-stricken counties. In 2017, JD.com launched a digital agricultural loan. Based on a quantitative model of agricultural production and the historical production data of farmers, it grants credit to farmers without collateral. In two years, this project has collaborated with more than 100 cooperatives in Shandong, Hebei, Henan, and others, providing loans of roughly 1 billion yuan, with a zero overdue rate (Jiang and Liu 2020).
a. http://www.mofcom.gov.cn/article/i/jyjl/l/202006/20200602969096.shtml. b. http://www.gov.cn/xinwen/2018–04/20/content_5284269.htm#2. c. http://www.xinhuanet.com/2018–06/06/c_1122943923.htm. d. AliResearch (Alibaba Group). “E-commerce for China’s Poverty Reduction: Research Report on E-commerce for Poverty Reduction and Inclusive Development” (电子商务助力中国减贫——电商减贫与普惠发展研究报告). August 30, 2017. e. Coverage is estimated by dividing the total number of online banking accounts in the rural area (612 million) by the total rural population of 968 million as of the end of 2018. However, one rural resident may own more than one online bank account (from different banks). It also depends on how the rural population is defined (given that there is a “floating” population that is counted as rural if holding rural hukou). A relevant Findex indicator is defined as “Used a mobile phone or the internet to access an account, rural (% age 15+).” China’s 2017 data have much lower coverage, at 35 percent. f. http://www.gov.cn/xinwen/2019–04/02/content_5378936.htm.
Although the targeted poverty reduction campaign has achieved its objectives, the data needed for a robust evaluation of its costs and benefits are currently not available. Given the sheer scale of resource mobilization from budgetary and nonbudgetary sources, the efficiency and sustainability of government efforts since 2013 is of particular interest. A first exploration in this direction is made by Freije-Rodriguez and Zhao (2021). Exploiting provincial-level data from 2010 through 2017, the authors aim to estimate the impact of public expenditure on poverty reduction programs and social assistance. They find that economic growth had less impact on poverty reduction in recent years, whereas antipoverty programs (funded through central and provincial governments’ antipoverty funds) had a positive effect. Nevertheless, the effect needs further study: a 10 percent increase in antipoverty funds per rural poor brings a poverty rate of reduction in the 0.16 to 0.77 percent range (Freije-Rodriguez and Zhao 2021, 45).19
Unfortunately, Freije-Rodriguez and Zhao are not able to break the effectiveness of government programs down into separate components, which would be of interest to draw more specific lessons for policy. Moreover, the analysis is not able to incorporate data on other government programs, such as subsidized loans or subsidies to education and agricultural inputs, that may be contributing to poverty reduction. By the same token, a large share of the funds mobilized under the government’s poverty eradication campaign have remained outside the budget system and are not well documented, further complicating an evaluation of the campaign’s efficiency and sustainability.
There is thus scope for more research going forward, to learn lessons from China’s success in reaching the goal of absolute poverty eradication. This is all the more important because China has decided to keep the levels of support to households that graduated from poverty in place for another five years to prevent any relapses into poverty. This volume returns to the question of
